Buzin Aline R, Pinto Fernanda E, Nieschke Kathleen, Mittag Anja, de Andrade Tadeu U, Endringer Denise C, Tarnok Attila, Lenz Dominik
University of Vila Velha, Pharmacology, Brazil.
University of Vila Velha, Pharmaceutical Sciences, Brazil.
J Immunol Methods. 2015 May;420:24-30. doi: 10.1016/j.jim.2015.03.011. Epub 2015 Mar 31.
The objective of the present study was to employ high throughput image analysis to detect necrosis and apoptosis. Specific markers were replaced by morphological parameters of cells and nuclei.
Fresh blood was taken from a healthy female and given a treatment to induce cell necrosis and apoptosis. Afterward, the samples were stained with AnnexinV-FITC, DRAQ5 and DAPI. Slides were made and analyzed using the cytometer iCys. Pictures were scanned. The analyzed sample consisted of 73 sets of images of DAPI, DRAQ5 and AnnexinV-FITC, respectively. For image analysis and subsequent statistical processing, the CellProfiler and CellProfilerAnalyst were used. Each sample was analyzed twice. The first analysis was conducted using the markers (DAPI, DRAQ5 and Annexin) for an unequivocal identification and subsequent count of necrotic, apoptotic and live cells (gold standard). Thereafter, a second analysis was performed for the nuclear morphology and texture (morphometric analysis). After the machine learning process was completed, the software calculated the quantity of cells in each of the three groups. A comparison between the result of the gold standard and the morphometric analysis was performed using linear regression and a Bland-Altman test.
The linear regression between the two compared analyses was r(2)=0.57 for apoptosis, r(2)=0.84 for necrosis and r(2)=0.79 for living cells.
It may be concluded that it is possible to replace specific markers against morphology without losing the reproducible high-throughput character of a cytometric analysis.
本研究的目的是采用高通量图像分析来检测坏死和凋亡。用细胞和细胞核的形态学参数取代特定标志物。
从一名健康女性采集新鲜血液，并进行处理以诱导细胞坏死和凋亡。之后，样本用膜联蛋白V-异硫氰酸荧光素（AnnexinV-FITC）、DRAQ5和4',6-二脒基-2-苯基吲哚（DAPI）染色。制作玻片并用iCys细胞仪进行分析。扫描图片。分析的样本分别由73组DAPI、DRAQ5和AnnexinV-FITC图像组成。为进行图像分析和后续统计处理，使用了CellProfiler和CellProfilerAnalyst。每个样本分析两次。第一次分析使用标志物（DAPI、DRAQ5和膜联蛋白）进行明确鉴定并随后计数坏死、凋亡和活细胞（金标准）。此后，对细胞核形态和纹理进行第二次分析（形态计量分析）。机器学习过程完成后，软件计算三组中每组的细胞数量。使用线性回归和布兰德-奥特曼检验对金标准结果和形态计量分析结果进行比较。
两种比较分析之间的线性回归对于凋亡r(2)=0.57，对于坏死r(2)=0.84，对于活细胞r(2)=0.79。
可以得出结论，在不丧失细胞分析可重复的高通量特性的情况下，有可能用形态学取代特定标志物。
